Patronus AI vs Promptfoo

Detailed side-by-side comparison to help you choose the right tool

Patronus AI

🔴Developer

AI Evaluation

Enterprise AI evaluation and safety platform with specialized Lynx and Glider evaluator models for RAG and agent quality.

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Starting Price

Free

🔴Developer

AI Evaluation

Open-source CLI and library for testing, evaluating, and red-teaming LLM prompts, models, and RAG pipelines — runs locally on your machine or in CI.

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Starting Price

Free

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Feature	Patronus AI	Promptfoo
Category	AI Evaluation	AI Evaluation
Pricing Plans	8 tiers	8 tiers
Starting Price	Free	Free
Key Features	• Evaluation and Quality Controls • Security and Governance • Observability	• Prompt and model evaluation • RAG pipeline testing • Automated red-teaming

✓Purpose-built evaluator models such as Lynx and Glider make Patronus more specialized than using a generic LLM judge for every quality check
✓Lynx is described as open weights, giving teams an option to inspect the hallucination-detection model rather than relying only on a closed hosted evaluator
✓Glider returns both scores and natural-language critiques, which helps reviewers understand why a response passed or failed instead of only seeing a numeric grade
✓Percival is positioned for agent failure localization, which is valuable when debugging multi-step workflows where the final answer alone does not reveal the root cause
✓The platform spans 3 important production needs in one workflow: evaluation and quality controls, security and governance, and observability
✓Compared to the 3 listed alternatives in this record, Patronus is especially strong for teams that need explainable evaluation outputs

✗Self-serve subscription pricing is limited; teams still need to contact sales for enterprise contract pricing and deployment terms
✗The platform is likely heavier than lightweight CI-only evaluation tools for small teams that only need prompt regression tests
✗Advanced capabilities such as Percival and custom evaluator training may require higher-tier or enterprise access
✗Model-based evaluation still requires representative datasets; poor test coverage can produce misleading confidence even with strong evaluator models
✗Teams in specialized domains may need calibration and human review because hallucination detection can miss subtle or context-dependent factual errors

✓Covers 6 product areas listed on the website: Red Teaming, Guardrails, Model Security, MCP Proxy, Code Scanning, and Evaluations.
✓Community plan is described as Free Forever and includes local or self-hosted operation, all LLM evaluation features, vulnerability scanning, and red teaming up to 10k probes per month.
✓Useful beyond prompt testing because it includes real-time guardrail positioning, model security monitoring, MCP Proxy protection, and IDE/CI/CD code scanning for LLM vulnerabilities.
✓Strong fit for regulated workflows because the website names 4 industry solution areas: Financial Services, Insurance, Telecommunications, and Real Estate.
✓Supports development workflows where evaluations and red-team checks can run before merge or release instead of relying only on post-deployment monitoring.
✓The site displays a public 20.6k metric alongside its open-source and community positioning, indicating substantial visible adoption or repository activity.

✗Public paid pricing is quote-based: Enterprise and On-Premise are listed as Custom rather than fixed monthly or annual prices.
✗The product surface is broad, so teams that only need simple prompt regression tests may find the security, guardrails, MCP proxy, and model-security positioning more than they need.
✗Red-teaming and evaluation quality still depend on well-designed test cases, assertions, graders, and representative datasets.
✗The website emphasizes development-time and security testing more than production observability, so teams may still need a tracing or monitoring platform alongside Promptfoo.
✗Enterprise suitability is clear, but self-serve details such as exact paid seat limits, usage caps beyond Community red-team probes, hosted data retention, and final contract terms are not visible in the public pricing content.

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